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Swapping Across 25 Models With One Line
Choosing a model is usually a commitment: an SDK, a key, an integration. Through the gateway it is a string, so you can shop the whole catalog per task. And the catalog spans a 100x price range, which turns model choice into your biggest cost lever. Here is the swap, the price spread, and a real multi-model run.
A Postgres-Backed MCP Server in ~20 Lines
Most of what an MCP server does is run database queries on behalf of an AI agent. So I put one right next to the database. Here is a Postgres-backed MCP server built on Neon Functions, deployed onto a database branch, with the code, a live client test, and the repo.
Compute That Lives on Your Database Branch
Neon Functions run your code in the same region as your Postgres, on a per-branch URL. To see why that matters I deployed a small API and timed a query from inside the function versus from a machine across the Atlantic: 1.2 ms against 135 ms. Here is how it works, with the real numbers and the repo.
Streaming an AI Agent Without a Function Timeout
Long agent loops and long token streams run into the same wall: a serverless function that hits its execution cap and cuts the connection. Neon Functions hold long-lived streaming connections by default. I deployed two endpoints to prove it: one streamed for 90 seconds, the other streamed an agent token by token starting at 466 ms.
I Gave an AI Agent a Database, Compute, Storage, and Models From One CLI
An AI agent usually needs four accounts: a database, somewhere to run, object storage, and a model provider. I wired all four from a single Neon credential and had a deployed image-generating agent in a few minutes. Here is the actual build log, the config that ties it together, and the honest caveats.
Neon Is Becoming a Backend Platform, Not Just Postgres
In June 2026 Neon added serverless functions, S3-compatible object storage, and an AI gateway to its database. The interesting part is not any one feature, it is the through-line: everything branches with your data. Here is what shipped, what it competes with, and where the seams still show.
Neon vs Supabase in Production: We Benchmarked the Operations That Page You at 3am
Two benchmark sessions against Neon and Supabase Pro measured what spec sheets never show: compute resizes cost 39 seconds of real downtime on one platform and zero on the other, read replicas differ by 23x, and branch creation has a tail you should know about.
Neon vs Supabase Pricing: What the Same App Costs From Launch to Scale
We priced one application through five growth stages on both platforms using verified June 2026 list prices. The result is three distinct cost regimes, two crossover points, and a surprise: at scale the biggest line item is not the database.
Neon vs Supabase Free Tiers: We Benchmarked Both So You Don't Have To
We ran 320 timed operations against the Neon and Supabase free tiers from a same-region client: query latency, project creation, cold starts, and branching. The latency race is a tie, and the real differences are nothing like the marketing.